Dear all,
I have a dataset and my model assumes that one variable mediates between 10 independent variables and 1 dependent variable. All 12 are observed. Furthermore, data was collected in two countries, so I have some nesting.
Let's say that X represents my set of 10 independent variables, and Y represents my dependent variable, and M represents my mediator.
Until now, I've been using the "mixed" regression command 4 times (Y on X, Y on M, M on X, Y on M and X) to determine mediation, as a first cut. But of course, this doesn't calculate the indirect effect properly (i.e. re: Mackinnon Type II errors). And not exactly state-of-the-art.
As you can see, I'm a bit new to testing mediation in STATA.
I explored a bit and found the medeff command but it can't handle nested data, right?
I could really use some advice. (I'd like to stay away from SEM if possible.)
Regards, -Chih
I have a dataset and my model assumes that one variable mediates between 10 independent variables and 1 dependent variable. All 12 are observed. Furthermore, data was collected in two countries, so I have some nesting.
Let's say that X represents my set of 10 independent variables, and Y represents my dependent variable, and M represents my mediator.
Until now, I've been using the "mixed" regression command 4 times (Y on X, Y on M, M on X, Y on M and X) to determine mediation, as a first cut. But of course, this doesn't calculate the indirect effect properly (i.e. re: Mackinnon Type II errors). And not exactly state-of-the-art.
As you can see, I'm a bit new to testing mediation in STATA.
I explored a bit and found the medeff command but it can't handle nested data, right?
I could really use some advice. (I'd like to stay away from SEM if possible.)
Regards, -Chih
Comment